Title
Stochastic Game Analysis of Cooperation and Selfishness in a Random Access Mechanism
Date Issued
01 March 2022
Access level
open access
Resource Type
journal article
Author(s)
Universidad de Castilla-La Mancha
Publisher(s)
MDPI
Abstract
This paper introduces a general stochastic game analysis of a network scenario consisting of a mix of cooperative and non-cooperative players (i.e., users) under incomplete game information. Users access a shared channel using the Slotted ALOHA mechanism combined with ZigZag Decoding (SAZD). Cooperative players seek to optimize the global utility of the system (e.g., throughput, delay, loss rate) regardless of their individual interests, whereas non-cooperative players act selfishly and optimize their own benefits irrespective of the impact of this behavior on others and on the entire network system. The game equilibrium is characterized by the social optimum and the Nash equilibrium, where the former is adopted by cooperative players and the latter is the equilibrium strategy of non-cooperative players. We undertake a comparative study across two game scenarios with different levels of cooperation and selfishness. Our results generally show that the information possessed by a player can determine the outcome. Furthermore, our findings show that the network performance is strongly influenced by selfish behavior, which can lead to a significant disruption of the entire system. Finally, we show a possible scenario in which the network could greatly benefit from this selfish behavior thanks to the ZigZag scheme.
Volume
10
Issue
5
Language
English
OCDE Knowledge area
Ingeniería de sistemas y comunicaciones
Subjects
Scopus EID
2-s2.0-85125450142
Source
Mathematics
ISSN of the container
22277390
Sponsor(s)
Funding: This work was supported by the Spanish Ministry of Science, Education and Universities, the European Regional Development Fund and the State Research Agency, Grant No. RTI2018-098156-B-C52. The first author was supported by the Erasmus+ program KA107.
Sources of information:
Directorio de Producción Científica
Scopus